The use of voice compression algorithms in communication systems that transmit voice messages is well known in the art. These algorithms are used primarily to minimize air-time transmission, thereby increasing bandwidth utilization. As a result of improved bandwidth utilization, the service provider of the communication can provide service to a larger population of subscribers at a lower cost.
Generally, voice compression algorithms are used in communication systems to accomplish two goals: (1) to compress an caller's voice message to the extent that a minimal transmission bit rate is achieved, and (2) to allow a subscriber unit of the communication system to substantially replicate the caller's voice message according to the caller's original voice characteristics with minimal distortion.
Ordinarily, voice signals are sampled at a bit rate of 64,000 bits per second. The industry-wide voice compression standard known as VSELP (Vector Summation Excitation Linear Prediction) utilized by, e.g., cellular service providers, for example, provides a compression rate of 6400 bits per second. Hence, this algorithm compresses an ordinary voice signal by a factor of 10, which amounts to 10 times the capacity of a communication system utilizing no compression. In addition to furnishing this compression rate, the VSELP algorithm provides a method at the subscriber unit for substantially replicating the speaker's original voice characteristics, thereby permitting the user of the subscriber unit to recognize who the caller is without prior identification.
Clearly, VSELP, and other comparable compression algorithms, are useful in improving bandwidth utilization in a communication system. However, because these algorithms attempt to preserve the caller's original voice characteristics, the rate of compression achievable is substantially limited by the maximum degree of distortion desired during the uncompression process at the subscriber unit.
Accordingly, what is needed is an apparatus and method for compressing voice messages at substantially higher rates than is provided by present prior art voice compression algorithms.